CA1 network model for place cell dynamics (Turi et al 2019)

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Biophysical model of CA1 hippocampal region. The model simulates place cells/fields and explores the place cell dynamics as function of VIP+ interneurons.
1 . Turi GF, Li W, Chavlis S, Pandi I, O’Hare J, Priestley JB, Grosmark AD, Liao Z, Ladow M, Zhang JF, Zemelman BV, Poirazi P, Losonczy A (2019) Vasoactive Intestinal Polypeptide-Expressing Interneurons in the Hippocampus Support Goal-Oriented Spatial Learning Neuron
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Hippocampus; Mouse;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell; Hippocampus CA1 basket cell; Hippocampus CA1 basket cell - CCK/VIP; Hippocampus CA1 bistratified cell; Hippocampus CA1 axo-axonic cell; Hippocampus CA1 stratum oriens lacunosum-moleculare interneuron ; Hippocampal CA1 CR/VIP cell;
Channel(s): I A; I h; I K,Ca; I Calcium; I Na, leak; I K,leak; I M;
Gap Junctions:
Receptor(s): GabaA; GabaB; NMDA; AMPA;
Simulation Environment: NEURON; Brian;
Model Concept(s): Place cell/field;
Implementer(s): Chavlis, Spyridon [schavlis at]; Pandi, Ioanna ;
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; GabaA; GabaB; AMPA; NMDA; I A; I K,leak; I M; I h; I K,Ca; I Calcium; I Na, leak;
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
Created on Wed Mar 15 15:21:06 2017

@author: spiros

def peakdet(v, delta, threshold, x = None):
    import sys
    import numpy as np
    Converted from MATLAB script at

    Returns two arrays

    function [maxtab, mintab]=peakdet(v, delta, x)
    %PEAKDET Detect peaks in a vector
    %        [MAXTAB, MINTAB] = PEAKDET(V, DELTA) finds the local
    %        maxima and minima ("peaks") in the vector V.
    %        MAXTAB and MINTAB consists of two columns. Column 1
    %        contains indices in V, and column 2 the found values.
    %        With [MAXTAB, MINTAB] = PEAKDET(V, DELTA, X) the indices
    %        in MAXTAB and MINTAB are replaced with the corresponding
    %        X-values.
    %        A point is considered a maximum peak if it has the maximal
    %        value, and was preceded (to the left) by a value lower by
    %        DELTA.

    % Eli Billauer, 3.4.05 (Explicitly not copyrighted).
    % This function is released to the public domain; Any use is allowed.

    maxtab = []
    mintab = []

    if x is None:
        x = np.arange(len(v))

    v = np.asarray(v)

    if len(v) != len(x):
        sys.exit('Input vectors v and x must have same length')

    if not np.isscalar(delta):
        sys.exit('Input argument delta must be a scalar')

    if delta <= 0:
        sys.exit('Input argument delta must be positive')

    mn, mx = np.Inf, -np.Inf
    mnpos, mxpos = np.NaN, np.NaN

    lookformax = True

    for i in np.arange(len(v)):
        if v[i] >= threshold:
            this = v[i]
            if this > mx:
                mx = this
                mxpos = x[i]
            if this < mn:
                mn = this
                mnpos = x[i]

            if lookformax:
                if this < mx-delta:
                    maxtab.append((mxpos, mx))
                    mn = this
                    mnpos = x[i]
                    lookformax = False
                if this > mn+delta:
                    mintab.append((mnpos, mn))
                    mx = this
                    mxpos = x[i]
                    lookformax = True

    return np.array(maxtab), np.array(mintab)

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